DOS Dataset: A Novel Indoor Deformable Object Segmentation Dataset for Sweeping Robots

Path planning for sweeping robots requires avoiding specific obstacles, particularly deformable objects such as socks, ropes, faeces, and plastic bags. These objects can cause secondary pollution or hinder the robot’s cleaning capabilities. However, there is a lack of specific datasets for deformable obstacles in indoor environments. Existing datasets either focus on outdoor scenes or lack semantic segmentation annotations for deformable objects. In this paper, we introduce the first dataset for detecting and segmenting deformable objects in indoor sweeping robot scenarios, DOS Dataset. We believe that DOS will catalyze research in semantic segmentation of deformable objects for indoor robot obstacle avoidance applications.